Re: [R] Efficient way to subset rows in R for dataset with 10^7 columns

Oh, there are ways, but the constraining issue here is moving data (memory bandwidth), and data table is probably already the fastest mechanism for doing that. If you have a computer with four or more real cores you can try setting up a subset of the columns in each task and cbind the results

Re: [R] Bivariate Normal Distribution Plots

Try this code: # Standard deviations and correlation sig_x <- 1 sig_y <- 2 rho_xy <- 0.7 # Covariance between X and Y sig_xy <- rho_xy * sig_x *sig_y # Covariance matrix Sigma_xy <- matrix(c(sig_x ^ 2, sig_xy, sig_xy, sig_y ^ 2), nrow = 2, ncol = 2) # Load the mvtnorm package

Re: [R] Efficient way to subset rows in R for dataset with 10^7 columns

You have 10^7 columns? That process is bound to be slow. On April 13, 2018 5:31:32 PM PDT, Jack Arnestad wrote: >I have a data.table with dimensions 100 by 10^7. > >When I do > >trainIndex <- > caret::createDataPartition( >df$status, >p = .9, >

[R] Efficient way to subset rows in R for dataset with 10^7 columns

I have a data.table with dimensions 100 by 10^7. When I do trainIndex <- caret::createDataPartition( df$status, p = .9, list = FALSE, times = 1 ) outerTrain <- df[trainIndex] outerTest <- df[-trainIndex] Subsetting the rows of df takes

[R] Extracting specified pages from a lattice ("trellis") object.

Suppose that (e.g.) xyplot() returns an object "xxx" with (say) 3 pages. I would like to extract/plot (print) just one of these pages, e.g. page 2. Here's a toy example: x <- rep(seq(0,1,length=11),12) set.seed(42) y <- rnorm(3*44) a <- rep(letters[1:12],each=11) dta <-

[R] cvTools for 2 models not working

Dear R-experts, I am trying to do cross-validation for different models using the cvTools package. I can't get the CV for the "FastTau" and "hbrfit". I guess I have to write my own functions at least for hbrfit. What is going wrong with FastTau ? Here below the reproducible example. It is a

Re: [R] Reading xpt files into R

> On Apr 13, 2018, at 10:01 AM, WRAY NICHOLAS via R-help > wrote: > > Hello R folk > > I have an xpt file which I have been trying to open into R in R studio > > On the net I found guidance which says that I need packages Hmisc and > SASxport which I have successfully

[R] SparksR

R-Help I'm working in my first large database (53,098,492,383 records). When I select the db via something like Library(SparkR) mydata <- sql("SELECT * FROM ") is "mydata" a SparkDataFrame, and do I work with SparkDataFrames like I would regular df (per say); because I can't image I

[R] Longitudinal and Multilevel Data in R and Stan: 5-day workshop May 28 to June 1, 2018

Longitudinal and Multilevel Data in R and Stan ICPSR short course: May 28 to June 1, 2018 May 28: Introduction to R by John Fox May 29 to June 1: Longitudinal and Multilevel Data in R and Stan by Georges Monette Sponsored and organized by ICPSR, University of Michigan and held at York

[R] Reading xpt files into R

Hello R folk I have an xpt file which I have been trying to open into R in R studio On the net I found guidance which says that I need packages Hmisc and SASxport which I have successfully loaded. I had also found some code which says that this would allow me to read the xpt file into R:

Re: [R] Fwd: R Timeseries tsoutliers:tso

You can record the time to evaluate each line by wrapping each line in a call to system.time(). E.g., expressions <- quote({ # paste your commands here, or put them into a file and use exprs <- parse("thatFile") d.dir <- '/Users/darshanpandya/xx' FNAME <- 'my_data.csv' d.input <-

[R] Fwd: R Timeseries tsoutliers:tso

Hello, Writing to seek help in regard to some unexpected performance anomaly i am observing in using tsoutlers:tso on the mac vs on an AWS cloud server.. I am running the following code with very small dataset of about 208 records. d.dir <- '/Users/darshanpandya/xx' FNAME <- 'my_data.csv'